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Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegenerationNARA Subscribed
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can fi...
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion te...
Dispersal of marine plastic litter during tropical cyclonesNARA Subscribed
Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learningNARA Subscribed
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, th...
Reconstructions of palaeo‐sea level are vital for predicting future sea level change and constraining palaeo‐ice sheet reconstructions, as well as being useful for a wide array of applications across Quaternary Science. Previous reconstructions of the palaeo‐sea level of Britain and Ireland relied on a circular tuning of glacio‐isostatic models: input ice sheet thicknesses and extents were iteratively altered to fit relative s...
Applying Mendelian randomization to appraise causality in relationships between nutrition and cancerNARA Subscribed
Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid c...
Knowledge of regional changes in mean sea level and local changes in tides are crucial to inform effective climate adaptation. An essential element is the availability of accurate observations of sea level. Sea level data in the Republic of Ireland, prior to the establishment of the National Tide Gauge Network in the mid-2000s, are limited but belie a wealth of historical data available in archival form. In this study, we digi...
A Brief Educational Intervention Enhances Basic Cancer Literacy Among Kentucky Middle and High School StudentsNARA Subscribed
Kentucky experiences the highest overall cancer incidence and mortality rates in the USA with the greatest burden in the eastern, Appalachian region of the state. Cancer disparities in Kentucky are driven in part by poor health behaviors, poverty, lack of health care access, low education levels, and low health literacy. Individuals with inadequate health literacy are less likely to participate in preventive measures such as o...
Key message β-Carotene content in sweetpotato is associated with the Orange and phytoene synthase genes; due to physical linkage of phytoene synthase with sucrose synthase , β-carotene and starch content are negatively correlated. Abstract In populations depending on sweetpotato for food security, starch is an important source of calories, while β-carotene is an important source of provitamin A. The negative association betwee...
Simultaneous‐count models to estimate abundance from counts of unmarked individuals with imperfect detectionNARA Subscribed
We developed a method to estimate population abundance from simultaneous counts of unmarked individuals over multiple sites. We considered that at each sampling occasion, individuals in a population could be detected at 1 of the survey sites or remain undetected and used either multinomial or binomial simultaneous‐count models to estimate abundance, the latter being equivalent to an N‐mixture model with one site. We tested mod...
The interplay of eustatic and isostatic factors causes complex relative sea‐level (RSL) histories, particularly in paraglacial settings. In this context the past record of RSL is important in understanding ice‐sheet history, earth rheology and resulting glacio‐isostatic adjustment. Field data to develop sea‐level reconstructions are often limited to shallow depths and uncertainty exists as to the veracity of modelled sea‐level...
Non-Invasive Multimodality Imaging Directly Shows TRPM4 Inhibition Ameliorates Stroke Reperfusion InjuryNARA Subscribed
The transient receptor potential melastatin 4 (TRPM4) channel has been suggested to play a key role in the treatment of ischemic stroke. However, in vivo evaluation of TRPM4 channel, in particular by direct channel suppression, is lacking. In this study, we used multimodal imaging to assess edema formation and quantify the amount of metabolically functional brain salvaged after a rat model of stroke reperfusion. TRPM4 upregula...
Motivation The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal...